Movie Review: Kiki's Delivery Service

Kiki’s Delivery Service (or Majo no Takkyubin, in Japanese) is a Studio Ghibli animated movie, written, produced, and directed by Hayao Miyazaki. This movie was released in 1989 - before I was born. But, like the other Studio Ghibli movies I’ve seen, it still seems so ahead of its times.

This movie is about Kiki, a 13 year old witch, who, according to tradition, has to move away from her family in order to train herself and become independent. But even as a nearly 30 year old woman, I can relate to it.

Kiki arrives in a new town with her black cat, Jiji, and sets up a delivery service. Through her adventures in this new city, the movie shows Kiki meeting wonderfully kind women, pulling and pushing each other up. I haven’t come across many movies with such splendid female characters. (And this was in 1989, folks!)

100 Days of Github. Take 2 Spillover, Day 61

Day 61

Suppose I want to generate random numbers that are drawn from a discrete power-law distribution. This is how I'll do it.
Again, if the github link doesn't work, click here.
Note that I need to finish notes for this notebook...

100 Days of Github. Take 2 Spillover, Day 60

Day 60

Some preliminary notes for the continuous power-law distribution, here.
Note: for some reason, some of the equations aren't rendering in when viewing the notebook directly form github.

100 Days of Github. Take 2 Spillover, Day 59

Day 59

Suppose I want to generate random numbers that are drawn from a continuous power-law distribution. How do I do that? This is how.
(If the earlier link doesn't work, click here.)

100 Days of Github. Take 2 Spillover, Day 58

Day 58

Code snippet to calculate degree distribution of given network. My earlier code barfed out all the degrees for which counts were zero, along with the others. This one doesn't.
Here, have a look.

100 Days of Github. Take 2 Spillover, Days 56, 57

Days 56, 57

Fitting exponential and power law with python for dummies.
Here and here.

100 Days of Github. Take 2 Spillover, Days 53, 54, 55

Days 53, 54, 55

In the midst of covid19, I decided to learn some network epidemiology.
So, to start this off, check links here, here, and here for some playing around with the SIR model.
And, the following is an eye-catching plot you see in the news these days: